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State Bank of India recently established a new policy linking savings account interest rates to Repo rates.

Hence the regression line Y = 0.52 + 1.20 * X Example #2 Let’s now input the values in the regression formula to get regression. We have all the values in the above table with n = 5. The term ‘b’ in the formula is the slope which signifies how much the dependent variable is upon the independent variable. It means that the value remains fixed irrespective of changes in the independent variable. read more if X, an independent variable, changes by a certain value. The objective of the FV equation is to determine the future value of a prospective investment and whether the returns yield sufficient returns to factor in the time value of money. Y is the dependent variable in the formula, which one tries to predict what will be the future value Future Value The Future Value (FV) formula is a financial terminology used to calculate cash flow value at a futuristic date compared to the original receipt. For example, the equation for a line is y = a + bX. Linear analysis is one type of regression analysis.

Regression analysis, as mentioned earlier, is majorly used to find equations that will fit the data.

Then one would use it to model the future relationship between those variables. read more is a powerful tool as it assesses the strength of the relationship between two or more variables. It is widely used in investing & financing sectors to improve the products & services further. Regression Regression Regression Analysis is a statistical approach for evaluating the relationship between 1 dependent variable & 1 or more independent variables. Regression analysis widely used statistical methods to estimate the relationships between one or more independent variables and dependent variables. It is represented by equation Y is equal to aX plus b where Y is the dependent variable, a is the slope of the regression equation, x is the independent variable, and b is constant. The regression formula assesses the relationship between the dependent and independent variables and finds out how it affects the dependent variable on the change of the independent variable.